CISE RR: Infrastructure to Support Heterogeneous and Dynamic Sensor Networking Research

该项目解决了异构和动态传感器技术，促进了实验研究，演示和分发支持混合传感器技术的可扩展中间件服务，包括传统的标量传感器，如Berkeley motes，以及较新的传感器，如OGI panoptes视频传感器。工作重点是以下任务：自适应网络协议、全局电源管理和可编程架构。通过动态推断和利用网络组件的异质性，第一个任务通过设计网络资源管理和数据恢复的自适应协议来研究支持一系列传感器网络技术的机制。第二部分研究了帮助设计人员理解异构传感器网络应用中的全局电源管理的技术。第三项任务研究中间件，以支持基于视频的传感器网络中混合信令的可编程性。为了验证和演示该方法，将构建三个示例应用程序。用于海岸监控（用于感知光线）、安全监控（用于感知房间内的运动）和医疗监控（用于验证视频，反之亦然）的时间流逝成像。将在每种情况下测量定制应用程序和中间件版本之间的各种参数的差异，以及通过混合传感器协同工作（而不是自主工作）来管理电源可以节省多少能源。本项目探讨了实现此类应用的基本挑战。解决传感器的多样性对于解决未来的传感器网络应用至关重要。这些系统包括不同类别传感器节点的集成和交互，激励方法需要节点之间比传统传感器网络中先前探索的更大的协同作用。通过使用各种附加传感设备的单独资金来增加基础设施，将能够创建一个广泛而灵活的测试平台，以研究支持混合技术的可扩展中间件服务。混合传感器技术可以丰富传感器应用的潜力。更广泛的影响：本研究的成果将对更广泛的社区有用；实际应用的经验可以为进一步的研究提供信息。此外，实验研究将进一步使环境科学和生物医学工程系的科学家。这项工作加强了课程，使学生能够参与实验传感器网络的研究，为他们的课程作业。

This project, addressing heterogeneous and dynamic sensor technologies, facilitates experimental research, demonstrating and distributing scalable middleware services that support hybrid sensor technologies, including traditional scalar sensors such as the Berkeley motes, as well as newer sensors such as the OGI panoptes video-based sensors. The work focuses on the following tasks: Adaptive Network Protocols, Global Power Management, and Programmable Architectures.Dynamically inferring and exploiting the heterogeneity of network components, the 1st task investigates mechanisms to support a range of sensor networking technologies by designing adaptive protocols for network resource management and data recovery. The 2nd investigates techniques to help designers understand global power management in heterogeneous sensor networking applications. The 3rd task investigates middleware to support the programmability of hybrid signaling within video-based sensor networks. To validate and demonstrate the approach, three sample applications will be built. Time-Elapsed Imaging for Coastal Monitoring (used to sense light), Security Monitoring (used to sense movement in a room), and Health-Care Monitoring (used to validate video and vice versa with scalars).The difference between a custom-built application and a middleware version for various parameters will be measured in each case, as well as how much energy can be saved by having hybrid sensors working cooperatively (rather than autonomously) to manage power. This project explores the fundamental challenges in enabling such applications. Addressing the diversity in sensors should be critical in addressing the sensor networking applications of the future. These systems comprise the integration and interaction of diverse classes of sensor nodes, motivating approaches that require greater synergy among nodes than those previously explored in the traditional sensor networks. Augmenting the infrastructure through separate funds with a variety of additional sensing devices, will enable the creation of an extensive and flexible testbed to study scalable middleware services that support hybrid technologies. Hybrid sensor technologies can enrich the potential of sensor applications.Broader Impact: The artifacts of this research will be useful to the broader community; the experiences with real applications can inform further research. Moreover, the experimental research will further enable scientists in the Environmental Science and Biomedical Engineering Departments. This work enhances the curriculum enabling students to partake in experimental sensor networks research for their course work.